Knowing the state of charge of a battery is necessary for an indication of how much longer a battery will continue to perform prior to the need for either recharging or replacement. As technologies related to vehicles continue to advance, the significance of understanding and monitoring battery life becomes increasingly significant.
Battery charge can be measured through several methods, such as chemically, through measurements and plotting of curves related to discharge, or even using electrical modeling.
One known method of providing direct measurements is a method that converts a reading of the battery voltage to state of charge (SOC), using the known discharge curve (voltage versus SOC) of the battery. Using such a method SOC is graphed in relation to an open-circuit voltage (OCV) estimation which is the voltage at equilibrium and therefore current equals zero. With this method, however, the voltage reading is significantly affected by the battery current due to the battery's electrochemical kinetics as well as temperature, especially if the battery is not truly at rest when readings are made. Therefore such methods are often made more accurate by compensating the voltage reading with a correction term proportional to the battery current, and by using a look-up/reference table of the battery's open-circuit voltage estimation versus temperature.
In lithium iron phosphate batteries (LiFeP), regions of the SOC-OCV curve have large changes in SOC for small changes of OCV estimations. In these regions, voltage sensing inaccuracies, analog-to-digital (A/D) resolution, and controller area network (CAN) database resolution are some potential causes of SOC inaccuracy. There is a need in the art for systems and methods providing users with knowledge that an estimated SOC based on voltage in these regions may contain large errors and should not be used.
Current systems are exceedingly complex, and there is a need in the art for increased simplicity, efficiency and decreased errors. Specific embodiments described herein lead to improvements in SOC accuracy, charge termination consistency, capacity estimation, and energy delivery consistency.